1. Technical Field
This invention relates to a system and method for diagnosing joint conditions, and more particularly to a system and method for automatically analyzing vibrations from moving joints to classify joint conditions.
2. Discussion
The effective treatment of joint disease depends on an accurate diagnosis. Usually the most accurate diagnostic tool is direct viewing of the joint using invasive surgical techniques. Unfortunately, the risks and costs associated with surgical diagnostic techniques are prohibitive for all but the most serious categories of conditions. For example, arthroscopy of the knee typically costs between $5,000.00 and $7,000.00.
A second choice in joint diagnosis is the use of radiological imaging techniques. These include x-rays and Computed Tonography (CT) scans, magnetic resonance imaging (MRI) and ultrasound. These techniques are used with varying degrees of success. CT scans and MRI are relatively expensive (about $500-$1,500.00) and sometimes do not reveal adequate information about the condition of the joint to permit an accurate diagnosis. In brief, neither surgery nor imaging techniques offer an ideal joint diagnostic tool for many joint disorders.
A third technique for diagnosing joints relies on the interpretation of vibrations emitted by joints. In general, the term "auscultation" is used to describe any method of examination of the functions and conditions of the human body by the sounds or vibrations they produce. Physicians have listened to sounds and felt vibrations from human joints in diagnosing joint pathology for centuries. Unfortunately, this approach has often proved to be frequently inaccurate. This is primarily due to the subjective nature of the use of hands and ears as vibration sensors. Another difficulty has been the limitations of language in communicating the types of sounds generated from joints associated with particular joint diseases from one practitioner to another. Also, auscultation depends upon the widely varying expertise of the examiner. Thus, while the characterization of joint conditions by analyzing the sounds produced by the joint shows promise as a diagnostic tool, a more objective approach than simply listening to the sounds is required to achieve the desired levels of reliability.
To overcome the shortcomings of auscultation, techniques for electronically recording joint vibrations or sounds have been developed. Once recorded, a visual display of the sounds can be generated to provide a more objective means for comparing the sounds from a patient's joint with those of joints having known pathologies. The first attempts to record joint sounds utilized microphones attached to the skin adjacent the joint. One problem with the use of microphones has been the difficulty in distinguishing articular sounds from extrinsic sounds, such as snapping tendons, noise due to hand tremors, skin friction and common background noise. This is because microphones integrate sound arising from a region of space, lacking a focus point, and precise vibration measurement at a point. Also some low frequency joint vibrations are below the dynamic range of microphones and could not therefore be detected.
For these reasons, accelerometers (or velocity transducers) have replaced microphones as the preferred sensors for recording joint sounds. This is because accelerometers have the mechanical advantage of being able to detect the direct transmission of vibrations. An accelerometer consists of a case within which is a piezoelectric crystal that has a mass resting on it. This crystal reacts to acceleration by producing a minute electric charge between its top and bottom surfaces, due to the compression produced by the mass, which is directly proportional to the acceleration. As a result, accelerometers detect only localized vibration and are sensitive to activity of very small amplitude.
The accelerometer is the basis of the new technique for joint diagnosis called vibration arthrometry. With vibration arthrometry reliable recordings of joint sounds and vibrations can be recorded and displayed. Accurate diagnosis can often be accomplished by comparing the vibrations from a patient's joint with those previously recorded from joints having particular known conditions. Nevertheless, subjective visual evaluation of the vibration waveform is still required to classify the vibration patterns. Also, the visual recognition of patterns is sometimes anecdotal; a perceived waveform may be only coincidentally related to a specific condition.
To assist in visual analysis, various statistical techniques have been employed. These include multiregression analysis, autocorrelation, and fast fourier transform analysis. These techniques are used to find parameters (for example, related to frequency and amplitude) that assist in the classification of joint conditions by their vibration patterns. However, even these statistical techniques ultimately require human interpretation to arrive at an accurate classification and diagnosis of joint condition. Moreover, a relatively high level of expertise is usually required to accurately interpret the results, limiting the usefulness of these techniques for most clinicians.
Thus, it would be desirable to provide a diagnostic tool for classifying joint conditions which is non-invasive, inexpensive and easy to use. Further, it would be desirable to provide a joint diagnostic tool having these characteristics and which utilizes joint vibrations to arrive at a non-subjective joint disorder classification. Also, it would be desirable to provide technique for classifying joint conditions by the vibration patterns that can be utilized by persons without particular expertise in analyzing the joint vibrational patterns where the results do not depend upon the skill of the person conducting the test.